Joseph I. Tracy - US grants

Cigarette smoking increases cholinergic activity in the central nervous system and, as a result, may temporarily enhance certain cognitive functions, particularly those related to selective attention, attentional vigilance, the response components of rapid information processing, and effortful/controlled memory processes. The prevalence of cigarette smoking among patients with schizophrenia is high (74%-92%), raising the possibility that cigarette smoking is an adaptive response in these patients, rewarding for its ability to induce neurochemically-based, transient cognitive improvements. This project will test the relation between plasma cholinergic levels and the above cognitive functions. Cholinergic levels and cognitive performance will be observed under conditions of recent/acute cigarette smoking and recent smoking abstinence (12 hrs.) in a sample of moderate (n=15) and heavy (n=15) smokers who suffer from chronic schizophrenia. Non-smoking chronic schizophrenic patients (n=15) will serve as controls to estimate cognitive fluctuations independent of smoking Condition (acute/abstinent). A three group repeated measures design will be used (n=45). All patient/subjects will meet DSM-III-R criteria for chronic schizophrenia, be matched by age, gender and duration of illness, and be on a verified, stable haloperidol regimen. Data on the primary independent variable (plasma muscarinic receptor binding as an index of cholinergic activity) and dependent variable (cognitive performance) will be collected under each Smoking Condition. Heart rate monitoring will verify current smoking status (heart rate acceleration/deceleration associated with acute/abstinence conditions, respectively). Plasma haloperidol, nicotine, and cotinine levels will verify medication metabolism and recent smoking intensity. A smoking induced, cholinergically-driven enhancement of cognitive performance is hypothesized.

A recent study of selective attention operations in schizophrenia reported subtle right visual field (RVF) hemineglect in a sample of non- chronic schizophrenics (Posner et al, 1988). This finding stimulated speculation about specific lateralized lesions (left parietal and/or left anterior) and attentional operations (i.e., diminished left hemisphere ability to generate preparatory sets) in schizophrenia. These findings were also used to explain other attention abnormalities in schizophrenia (i.e., vigilance). Replication of this important finding is needed to ensure that model building activity in selective attention is on solid ground. Also, determination of the mechanism underlying the finding is needed for accurate neuroanatomical theory and further research on its diagnostic or etiologic value. Specifically, the hemineglect may be caused by a failure in stimulus selection, i.e., filtering, or an inability to generate attentional gradients, which play a key role in generating preparatory, expectational sets. Finally, the temporal stability of deficits in selective attention have not been established and their relation to neuroleptic medication and clinical state have yet to be defined. This project will replicate the Posner et al. (1988) study and assess performance on a shape identification, i.e., filtering, task (LaBerge and Brown, 1989) through a four group, repeated measures design (N=120; baseline, 3 and 6 month assessments). Chronic schizophrenics on one of three neuroleptic regimens (clozapine, risperidone, prolixin decanoate, n's=30) and normal controls (n=30) will be followed for six months. Patients will remain on the same neuroleptic throughout the study. Serial assessments will also be taken of psychiatric symptoms, cognitive status, and gross hemineglect. The three schizophrenic groups will be matched on duration of illness. All four groups will be matched on age and gender. The hemineglect hypothesis will be tested along with tests of an early filtering mechanism for visual shape, and the ability to generate attentional gradients.

[unreadable] DESCRIPTION (provided by applicant): The goal of the study is to detect Magnetic Resonance Imaging (MRI) evidence of correlated neural signalling in medial temporal lobe epilepsy (mTLE) patients consistent with epiletogenesis and then test for the cognitive effects of this potential brain circuit. The development of epileptiform activity remote from the epileptogenic region may facilitate correlated neural signalling between the affected brain regions. The location of new neural connections built up by epileptogenesis, while not completely random, are not constrained to make neuropsychological sense in terms of laying the neural groundwork for effective cognitive skill. This abnormal, correlated signal should create favored neural pathways that can be recruited by neurocognitive networks to cause maladaptive activation that reduces cognitive performance. When cells of the primary focus fire, activation in the newly built neural circuit should be potentiated. Therefore, it becomes possible to observe these aberrant connections not just during clinically observable seizure activity, but also during cognitive stimulation of the primary epileptogenic zone. MTLE patients with Unilateral (n=15) versus Bilateral (n=15) epileptic activity will be studied along with matched, healthy contols (n=15). The goals of the study are to: (1) test for functional connectivity between gray matter regions consistent with epileptogenesis, (2) provide evidence for the development of epilepsy- driven neural circuits and determine their impact on memory performance, (3) provide evidence that flawed task performance can emerge from the activation of disease-driven neural circuits. Two imaging modalities will be utilized. Functional Connectivity MR Analysis will be used to verify the functional connections, respectively, between the regions of interests (left and right medial temporal lobes in patients with mTLE). Functional MRI will be used to determine the presence of anomalous activation involving these mTL regions during the cognitive tasks that is consistent with epileptogenesis. The project offers the possibility of providing indirect evidence for epileptogenesis, specifying its cognitive effects, and offering a potential model for the development of cognitively ineffective and aberrant neural circuitry in adults as a result of neural disease. The data will have implications for theories of learning by demonstrating how disease-driven correlated neural signals can form maladaptive neurocognitive networks that detrimentally influence performance. Summary Developing multimodal brain imaging methods for confirming the presence or impact of additional epileptiform activity outside the primary seizure focus will help with accurate selection of candidates for focal epilepsy surgery, aid in the planning of potential staged surgeries, and influence informed consent regarding surgical risks such as potential cognitive deficits and the expected degree of seizure control. Evidence suggesting that the lesional epileptic zone initiated a circuit of maladaptive cognitive responses will increase the cognitive "cost" of the epilepsy and likely increase the need for surgical control of the seizures. Multimodal mapping of brain regional connectivity will improve localization of functionally intact cognitive networks, increase our ability to tailor the surgical resection to avoid these areas, and open up the benefits of epilepsy surgery to a wider range of patients who might have been excluded because of concerns over cognitive morbidity. [unreadable] [unreadable] [unreadable]

Project Summary For epileptic patients who undergo brain resection or ablation interventions, it is the postoperative brain that will dictate seizure status, whether controlled or relapsed. Yet, it is data from the preoperative brain that drives the postoperative prediction process ? a critical process for both patient and doctor, and one that is only clinically meaningful when seizure outcomes are predicted presurgically to optimize surgical-decision making. Accordingly, we propose to develop a multi-step model that will establish more accurate predictors of post- surgical seizure outcome in temporal lobe epilepsy (TLE) emphasizing post-surgical status, for it is the areas of the brain spared during surgery that form the neural substrates generating postoperative seizures. A second perspective motivating our project is the need to identify those changes in functional and structural brain network organization that support adaptive versus maladaptive seizure outcomes following brain surgery. These are the network changes (e.g., the new seizure generators) that dispose and place a potential surgical candidate on a specific outcome trajectory. Therefore, identifying the phenotypes of brain reorganization and change, and incorporating their status into presurgical predictive models of outcome will likely prove crucial to enhancing our ability to predict postoperative neuroplastic responses. While existing outcome prediction models in TLE have focused on clinical variables (e.g., lesional status), we choose instead to focus on structural and functional measures of network reorganization (communication dynamics, regional interactions, structural control). This stems from our belief that capturing network changes throughout the whole postsurgical brain offers a better practical method for identifying and predicting the latent seizure foci (epileptogenesis) that will emerge after surgery. Through machine learning techniques we will deliver an algorithm to be used with new, potential surgical patients, an algorithm that utilizes solely presurgical data, but incorporates our innovative prediction about postsurgical brain organization. Accordingly, our approach provides both a methodologic and conceptual (reorganization phenotypes) advance. The scientific premise leading to our hypotheses is that the failure in the literature to account for the impact of unresected/ablated brain regions, and the brain reorganizations these areas compel, has seriously impeded the predictive power of previous outcome models.